A Visual Walkthrough of DeepSeek’s Multi-Head Latent Attention (MLA) ‍♂️

Exploring Bottleneck in GPU Utilization and Multi-head Latent Attention Implementation in DeepSeekV2.

In this article, we’ll be exploring two key topics. First, we’ll discuss and understand the bottleneck problems that transformer models, also known as Large Language Models (LLMs), encounter during training and inference.

Then, we’ll delve into a specific bottleneck issue in LLM architectures regarding KV cache, and how DeepSeek’s innovative approach, Multi-Head Latent Attention, addresses this problem.

ai article artificial intelligence attention deep learning deepseek discuss gpu head image implementation inference key language language models large language large language models llms machine learning multi-head topics training transformer transformer models visual walkthrough